Supervised classifications using optical remote
sensing data have been used in the region of
Navarre (Spain) for many years to obtain data
for the elaboration of the annual crops statistics.
However, cloud cover very frequent in this
area limits and even prevents the use of optical
data for this scope. Radar remote sensing represents
an interesting alternative, since at its
wavelengths, t ...
[++]

Supervised classifications using optical remote
sensing data have been used in the region of
Navarre (Spain) for many years to obtain data
for the elaboration of the annual crops statistics.
However, cloud cover very frequent in this
area limits and even prevents the use of optical
data for this scope. Radar remote sensing represents
an interesting alternative, since at its
wavelengths, the cloud cover is transparent; not
implying any limitation. Furthermore, the new
generation of radar sensors (ALOS/PALSAR
and RADARSAT-2 for example), incorporate
significant improvements over their predecessors
(or ERS-1/-2 RADARSAT-1). Finally, for
crop classification, radar sensors that acquire
images in multiple polarizations are particularly
interesting.
The main objective of this study was to evaluate
the feasibility of polarimetric radar observations
for crop classifications in central Navarre.
For this, two ALOS/PALSAR observations
have been used. A detailed polarimetric analysis,
polarimetric signatures of different crops
under dryland and irrigation conditions were
the previous step to the supervised classification
performed. The result crop classification
was compared with reference ground data, obtaining
an overall Kappa and accuracy of 0.52
and 85% respectively. [--]